RESUMO
The current study aimed to identify therapeutic gene and microRNA (miRNA) biomarkers for diabetic kidney disease (DKD). The public expression profile GSE30122 was used. Following data preprocessing, the limma package was used to select differentially-expressed genes (DEGs) in DKD glomeruli samples and tubuli samples and they were compared with corresponding controls. Then overlapping DEGs in glomeruli and tubuli were identified and enriched analysis was performed. In addition, proteinprotein interaction (PPI) network analysis as well as subnetwork analysis was conducted. miRNAs of the overlapping DEGs were investigated using WebGestal. A total of 139 upregulated and 28 downregulated overlapping DEGs were selected, which were primarily associated with pathways involved in extracellular matrix (ECM)receptor interactions and cytokinecytokine receptor interactions. CD44, fibronectin 1, CC motif chemokine ligand 5 and CXC motif chemokine receptor 4 were four primary nodes in the PPI network. miRNA (miR)175p, miR20a and miR106a were important and nuclear receptor subfamily 4 group A member 3 (NR4A3), protein tyrosine phosphatase, receptor type O (PTPRO) and Kruppel like factor 9 (KLF9) were all predicted as target genes of the three miRNAs in the integrated miRNAtarget network. Several genes were identified in DKD, which may be involved in pathways such as ECMreceptor interaction and cytokinecytokine receptor interaction. Three miRNAs may also be used as biomarkers for therapy of DKD, including miR175p, miR20a and miR106a, with the predicted targets of NR4A3, PTPRO and KLF9.